A serverless, data-driven Git metrics dashboard using Amazon Quick Sight

This article demonstrates how to build a serverless Git metrics dashboard using AWS services to automatically collect development activity from GitHub and GitLab and visualize it with Amazon QuickSight.

• Automated event-driven pipeline collects repository metrics from GitHub and GitLab APIs on schedule
• Intelligent change detection skips processing if no repository changes detected since last collection
• Adaptive chunking automatically partitions workload for organizations with 20+ repositories using Step Functions Map states
• Full and incremental load strategies minimize API calls; full refresh triggered every 24 hours
• Metrics stored in S3 as JSON and CSV files, visualized through interactive QuickSight dashboards
• Architecture uses EventBridge Scheduler, Step Functions, Lambda, Secrets Manager, S3, and QuickSight
• Aligns with AWS AI-Driven Development Lifecycle framework for measuring AI tool effectiveness

The serverless solution provides near-real-time Git analytics with minimal operational overhead, enabling teams to track sprint velocity, assess release readiness, and quantify development improvements.